{"id":"W2562797673","doi":"10.1109/cdc.1999.832745","title":"Production and maintenance control for manufacturing system","year":2003,"lang":"en","type":"article","venue":"","topic":"Reliability and Maintenance Optimization","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Preventive maintenance; Failure rate; State (computer science); Production (economics); Markov process; Reliability engineering; Corrective maintenance; Computer science; Process (computing); Production control; Control (management); Jump; Engineering; Mathematics; Artificial intelligence; Statistics; Algorithm; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001241477,0.001077019,0.001026828,0.0005327013,0.0004935702,0.00134557,0.001070368,0.0008785195,0.002050736],"category_scores_gemma":[0.002233179,0.0003995971,0.0005282006,0.0005027398,0.0007472862,0.0007795711,0.0005680502,0.000796725,0.0002485382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001183553,"about_ca_system_score_gemma":0.0009367553,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006501503,"about_ca_topic_score_gemma":0.002559197,"domain_scores_codex":[0.9991322,0.000220136,0.00003200604,0.0002394362,0.0002215285,0.0001546183],"domain_scores_gemma":[0.9990249,0.0004613715,0.000257694,0.0000419025,0.0001719407,0.00004215598],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000985416,0.00006906797,0.0005470794,0.0001720139,0.00004314462,0.0001243226,0.00005486288,0.9647461,0.003166451,0.01082113,0.0009283141,0.01922895],"study_design_scores_gemma":[0.00001718731,0.0000706153,0.0003029329,0.000005275791,0.00001312798,0.0000200831,0.000005631185,0.9951481,0.0004867219,0.003594162,0.0003305838,0.000005466026],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07477037,0.001825766,0.9158018,0.000510506,0.0001244914,0.00009899986,0.0001460839,0.0003370513,0.006384909],"genre_scores_gemma":[0.9815136,0.0005494081,0.013645,0.00004226278,0.00007942522,0.00008791687,0.0001119453,0.00003601425,0.003934438],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006501503,"threshold_uncertainty_score":0.01292729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004385965844332355,"score_gpt":0.1699798835632062,"score_spread":0.1655939177188739,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}